What is Cancer?

Serdar Balcı, MD, Pathologist

What is Cancer?

Replication Crisis

https://en.wikipedia.org/wiki/Replication_crisis

Replication Crisis Excel Version

RStudio ile proje oluştur

R Notebook

R Notebook dökümanı oluşturma

R Notebook’tan html, pdf ve word oluşturma

RNotebook vs RMarkdown

https://youtu.be/zNzZ1PfUDNk

R Markdown

Hem kendi kodları hem de html kodları yazılabilir

https://rmarkdown.rstudio.com

What is R Markdown? from RStudio, Inc. on Vimeo.

R Markdown: The Definitive Guide

https://bookdown.org/yihui/rmarkdown/

R Markdown syntax

https://gist.github.com/MinhasKamal/7fdebb7c424d23149140

Remedy Package

Remedy

R Markdown paket ve şablonları

https://bookdown.org/yihui/rmarkdown/document-templates.html

Render Markdown via code

inside R

markdown::markdownToHTML('markdown_example.md', 
'markdown_example.html')

command line

R -e "markdown::markdownToHTML('markdown_example.md',
'markdown_example.html')"

pandoc Rstudio integration

command line

export PATH=$PATH:/Applications/RStudio.app/Contents/MacOS/pandoc
R -e "rmarkdown::render('markdown_example.md')"

RMarkdown chunk içinde R kodlarını çalıştırma

{r, results='asis'}
 iris %>%
  tibble::as_tibble() %>%
  details::details(summary = 'tibble')

Metin arasında R kodlarını çalıştırma

Chunk Options

Global Options

{r global_options, include=FALSE}
knitr::opts_chunk$set(fig.width = 12,
                      fig.height = 8,
                      fig.path = 'Figs/',
                      echo = FALSE,
                      warning = FALSE,
                      message = FALSE,
                      error = FALSE,
                      eval = TRUE,
                      tidy = TRUE,
                      comment = NA)

Other Code Languages

R Markdown kod örneği

{r}
data("cancer")
cancer
foreign::write.foreign(df = cancer,
                        datafile = "data/cancer.sav",
                        codefile = "data/cancer.spo",
                        package = "SPSS"
                        )

R Markdown Paket Çağırma 📦

{r}
suppressPackageStartupMessages(library("tidyverse"))
suppressPackageStartupMessages(library("survival"))

Sık kullandığım paketler 📦

{tidyverse} {tidylog}

{lubridate} {janitor}

{readxl} {foreign}

{summarytools} {ggstatsplot} {tangram} {finalfit} {psycho} {jmv}

{survival} {survminer}

{report} {kableExtra}

R Markdown Veri Yükleme SPSS

R Markdown Veri Yükleme Excel

Veri Görüntüleme

{r}
View(mydata)
glimpse(mydata)

Veri Düzenleme

{r}
mydata <- janitor::clean_names(mydata)
{r}
mydata$sontarih <- janitor::excel_numeric_to_date(
  as.numeric(mydata$olum_tarihi)
  )

Recode

{r}
mydata$Outcome <- "Dead"
mydata$Outcome[mydata$olum_tarihi == "yok"] <- "Alive"
{r}
## Recoding mydata$cinsiyet into mydata$Cinsiyet
mydata$Cinsiyet <- recode(mydata$cinsiyet,
               "K" = "Kadin",
               "E" = "Erkek")
mydata$Cinsiyet <- factor(mydata$Cinsiyet)

Recode regular expression

{r recode TNM stage}
#pT2N0Mx -> 2
mydata$Tstage <- stringr::str_match(
  mydata$patolojik_evre, 
  paste('(.+)', "N", sep=''))[,2]
)

Recode regular expression case_when

{r recode TNM2}
mydata <- mydata %>% 
    mutate(
        T_stage = case_when(
            grepl(pattern = "T1", x = .$Tstage) == TRUE ~ "T1",
            grepl(pattern = "T2", x = .$Tstage) == TRUE ~ "T2",
            grepl(pattern = "T3", x = .$Tstage) == TRUE ~ "T3",
            grepl(pattern = "T4", x = .$Tstage) == TRUE ~ "T4",
            TRUE ~ "Tx"
        )
    )

Recode regular expression case_when

{r}
mydata <- mydata %>% 
    mutate(
TumorPDL1gr1 = case_when(
        t_pdl1 < 1 ~ "kucuk1",
        t_pdl1 >= 1 ~ "buyukesit1"
    )
    )

R Markdown Tanımlayıcı İstatistikler

{r}
library(summarytools)
view(dfSummary(colon_s))

A beginner kit for #rstats The Landscape of R Packages for Automated Exploratory Data Analysis https://journal.r-project.org/archive/2019/RJ-2019-033/

@article{RJ-2019-033, author = {Mateusz Staniak and Przemysław Biecek}, title = {{The Landscape of R Packages for Automated Exploratory Data Analysis}}, year = {2019}, journal = {{The R Journal}}, doi = {10.32614/RJ-2019-033}, url = {https://journal.r-project.org/archive/2019/RJ-2019-033/index.html} }

Table One

{r, results='asis'}
# cat(names(mydata), sep = " + \n")
library(arsenal)
tab1 <- tableby(~ Cinsiyet + 
Yas + 
TumorYerlesimi
                ,
                data = mydata)
summary(tab1)

The Grammar of Tables

tangram: The Grammar of Tables

A grammar of tables

Grammar of Tables?

Easily generate information-rich, publication-quality tables from R

Kategorik Veriler

{r}
mydata %>% 
  janitor::tabyl(Categorical) %>%
  adorn_pct_formatting(rounding = 'half up',
                       digits = 1) %>%
  knitr::kable()
{r crosstable}
mydata %>%
    summary_factorlist(dependent = dependent, 
                       explanatory = explanatory,
                       total_col = TRUE,
                       p = TRUE,
                       add_dependent_label = TRUE) -> table
knitr::kable(table, row.names = FALSE, align = c('l', 'l', 'r', 'r', 'r'))

Kategorik Veriler için Grafikler

{r ggstatplot, layout='l-page'}
mydata %>% 
    ggstatsplot::ggbarstats(data = .,
                            main = Categorical_variable,
                            condition =  dependent_variable
                            )

Continious Variables

{r}
mydata %>% 
jmv::descriptives(
    data = .,
    vars = c(yas),
    hist = TRUE,
    dens = TRUE,
    box = TRUE,
    violin = TRUE,
    dot = TRUE,
    mode = TRUE,
    sd = TRUE,
    variance = TRUE,
    skew = TRUE,
    kurt = TRUE,
    quart = TRUE)

R Markdown örneği Çapraz Tablolar

{r crosstable}
library(finalfit)
mydata %>%
    summary_factorlist(dependent = dependent, 
                       explanatory = explanatory,
                       column = TRUE,
                       total_col = TRUE,
                       p = TRUE,
                       add_dependent_label = TRUE,
                       na_include=FALSE
                       # catTest = catTestfisher
                       ) -> table
knitr::kable(table,
             row.names = FALSE,
             align = c('l', 'l', 'r', 'r', 'r'))

R Markdown örneği Sağkalım

Sağkalım için veriyi düzenleme

{r define survival time}
mydata$int <- lubridate::interval(
  lubridate::ymd(mydata$CerrahiTarih),
  lubridate::ymd(mydata$SonTarih)
  )
mydata$OverallTime <- lubridate::time_length(mydata$int, "month")
mydata$OverallTime <- round(mydata$OverallTime, digits = 1)
{r}
## Recoding mydata$Outcome into mydata$Outcome2
mydata$Outcome2 <- recode(mydata$Outcome,
               "Alive" = "0",
               "Dead" = "1")
mydata$Outcome2 <- as.numeric(mydata$Outcome2)

Kaplan-Meier

{r Kaplan-Meier}
mydata %>%
  finalfit::surv_plot(dependent,
                      explanatory,
                      xlab='Time (months)',
                      pval=TRUE,
                      legend = 'none',
                      break.time.by = 12,
                      xlim = c(0,60),
                      legend.labs = c('a','b')
)

Sağkalım Tabloları

{r}
km_fit <- survfit(dependent ~ explanatory,
                  data = mydata)
km_fit
{r, eval=FALSE, include=FALSE}
library(survival)
km <- with(mydata, Surv(OverallTime, Outcome2))
# head(km,80)
# plot(km)
{r 1-3-5-yr}
summary(km_fit, times = c(12,36,60))

Pairwise comparison

{r}
survminer::pairwise_survdiff(formula = Surv(time, Outcome) ~ Group, 
                             data = mydata,
                             p.adjust.method = "BH")

Multivariate Analysis Survival

{r Multivariate Analysis, eval=FALSE, include=FALSE}
library(finalfit)
library(survival)
explanatoryMultivariate <- explanatoryKM
dependentMultivariate <- dependentKM
mydata %>%
  finalfit(dependentMultivariate, explanatoryMultivariate) -> tMultivariate
knitr::kable(tMultivariate, row.names=FALSE, align=c("l", "l", "r", "r", "r", "r"))

jamovi

jamovi ve R entegrasyonu

Rj Editor – Analyse your data with R in jamovi

{jmv} paket kodları

jamovi syntax mode

Güncellemeler olunca kodlar çalışacak mı?

Paket Kütüphaneleri

  • packrat / renv

https://environments.rstudio.com

Docker

  • docker

The Rocker Project

Docker Containers for the R Environment

docker run --rm -ti rocker/r-base

Or get started with an RStudio® instance:

docker run -e PASSWORD=yourpassword --rm -p 8787:8787 rocker/rstudio

and point your browser to localhost:8787 Log in with user/password rstudio/yourpassword

Managing containers

Yeni R sürümleri

  • RSwitch

https://rud.is/rswitch/

  • Using RSwitch

https://rud.is/rswitch/guide/

: scale 30%

Yedeklemeyi nasıl yapacağız

Projeyi düzgün organize edin

  • pdf
  • R
  • images
  • bib
{r load library}
source(file = here::here("R", "loadLibrary.R"))

Save Final Data

{r}
saved data after analysis to `mydata.xlsx`.

save.image(file = here::here("data", "mydata_work_space.RData"))

readr::write_rds(x = mydata, path = here::here("data", "mydata_afteranalysis.rds"))

saveRDS(object = mydata, file = here::here("data", "mydata.rds"))

writexl::write_xlsx(mydata, here::here("data", "mydata.xlsx"))

paste0(rownames(file.info(here::here("data", "mydata.xlsx"))), " : ", file.info(here::here("data", "mydata.xlsx"))$ctime)

GitHub Yedekleme

Her dökümanın sonuna kullandığınız kütüphaneler için atıf yazdırabilirsiniz

{r}
citation()

Libraries Used

citation()

To cite R in publications use:

  R Core Team (2019). R: A language and environment for
  statistical computing. R Foundation for Statistical Computing,
  Vienna, Austria. URL https://www.R-project.org/.

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2019},
    url = {https://www.R-project.org/},
  }

We have invested a lot of time and effort in creating R, please
cite it when using it for data analysis. See also
'citation("pkgname")' for citing R packages.

Bu oturuma spesifik kullanılan paketler

Tek tek paket atıfları

{r library citations}
citation("tidyverse")
citation("readxl")
citation("janitor")
citation("report")
citation("finalfit")
citation("ggstatplot")

Jamovi ve R için atıf örneği

Her dökümanın sonuna oturum detaylarınızı yazdırabilirsiniz

{r session info, echo=TRUE}
sessionInfo()

Session Info

sessionInfo()
R version 3.6.0 (2019-04-26)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS  10.15

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
 [1] compiler_3.6.0   magrittr_1.5     formatR_1.7      htmltools_0.4.0 
 [5] tools_3.6.0      yaml_2.2.0       Rcpp_1.0.2       codetools_0.2-16
 [9] stringi_1.4.3    rmarkdown_1.16   rmdshower_2.1.1  knitr_1.25      
[13] stringr_1.4.0    xfun_0.10        digest_0.6.21    rlang_0.4.1     
[17] evaluate_0.14

Sonraki Konular

  • RStudio ile GitHub kullanımı
  • …

Önerilen Kaynaklar

Sunum Linkleri

https://sbalci.github.io/MyRCodesForDataAnalysis/R-Markdown.nb.html https://sbalci.github.io/MyRCodesForDataAnalysis/R-Markdown.html

https://forms.gle/UqGJBiAjB8uLPRon8

Geri Bildirim

İletişim

Completed on 2019-11-01.

Serdar Balci, MD, Pathologist

https://rpubs.com/sbalci/CV
https://sbalci.github.io/
https://github.com/sbalci
https://twitter.com/serdarbalci